It would be nice if someone could compare these commercially available APIs with Yahoo's open_nsfw model in terms of accuracy: https://github.com/yahoo/open_nsfw
I'm currently building an API wrapper around it and running it on a Hetzner server with a GTX 1080 - prediction takes about 0.25 seconds and while I haven't optimised it for parallel execution, I think it should be able to handle at least +10 images/sec comfortably. I'm also testing video moderation by using ffmpeg to slice the video into screenshots and predicting the min/avg/high scores.
Moderating 25 million explicit images using Google Cloud Vision would cost around $19,500/mo vs €99/mo on Hetzner.
Makes a lot of sense, actually its really difficult to get a large enough dataset for moderation tasks to make a decent inhouse model for a fair enough comparison.
Sure, we can try scraping that from pornhub etc but fee then the negative classes would be very domain specific, using stock images may not provide a good measure.
Also, its really weird to assign such a task to any of your employees, feels kinda strange :)
Yeah, it's definitely not a nice task but what's stopping someone (well, besides potential legal issues) from using these commercial APIs to create datasets programatically and training a cloned model from that?
I'm curious what the profit margins are on these APIs because I think they are way overpriced.
I tried out various image labeling APIs, including Google Vision (Safe Search) for exactly this use case (moderation). I was honestly astonished at the pricing of these APIs. Google is somewhere at 1.50€ for 1000 images which is - imo - very expensive. I tried out the default models that come with Tensorflow but well, they are trained on scientific datasets which typically involve species and flowers - no luck there either. Any good tips for pre-trained models that solve this (for tensorflow)?
For those interested, PixLab let you analyze 50K images or video frames via its /nsfw endpoint for $25. They charge $0.9 per 1000 requests after you reach this quota.
BTW we had a question in general to anyone who can help us,
Does hosting such a dataset cause issues with SEO etc? Anything else we should be aware of?
I'm currently building an API wrapper around it and running it on a Hetzner server with a GTX 1080 - prediction takes about 0.25 seconds and while I haven't optimised it for parallel execution, I think it should be able to handle at least +10 images/sec comfortably. I'm also testing video moderation by using ffmpeg to slice the video into screenshots and predicting the min/avg/high scores.
Moderating 25 million explicit images using Google Cloud Vision would cost around $19,500/mo vs €99/mo on Hetzner.